University of Delaware · Dept. of Political Science & International Relations
We study ENVIRONMENT_ through data and AI.
74
Publications
selected research outputs
5
Research Themes
in computational pol. sci.
13
Team Members
current & alumni
10
Active Projects
current & upcoming
Research Themes
SADL's work spans five interconnected domains in computational political science, linked by rigorous data collection and reproducible methods.
Data-driven work on environmental movements, climate negotiations, climate shocks, and environmental governance.
Computational analysis of manipulated media, misinformation tactics, political communication, and online information systems.
Research on public accountability, access-to-information requests, government disclosure, and bureaucratic responsiveness.
Studies of conflict, repression, human rights monitoring, food insecurity, and violence against civilians.
Computational social science methods for political data, including text-as-data, event data, and statistical modeling.
Active Research
Figure (cropped): Almquist, Bagozzi, Blinova & Brown (2026), Network Science 14:e7, Fig. 2(c), CC BY 4.0
Environmental Politics
Research on participation, organizational diversity, value networks, and negotiation dynamics across more than 30 years of international climate change talks.
Related publications
In Search of Common Ground: Exploring Value Networks at the UNFCCC Climate Change Talks; Dynamic Networks of Negotiation for International Climate Change Cooperation
Figure: Blinova, Emuru, Emuru & Bagozzi (2026), Scientific Data 13:493, Fig. 1, CC BY-NC-ND 4.0
Environmental Politics
Geo-located attendance data and research on participation in Convention on International Trade in Endangered Species conferences of the parties.
Related publications
Geo-Located Attendance Data for CITES Conferences of the Parties
Photo: Bahnfrend / Wikimedia Commons, CC BY-SA 4.0
Computational Methods
Linked multi-modal data (texts, images, and captions) for studying Russian domestic and foreign policy speeches with computational methods.
Research Support
Current support for SADL research, data infrastructure, and student collaboration.
National Science Foundation
NSF OAC-2417814 supports a regional computational and data-intensive research workforce and network from 2024 through 2029. The award is led by PI Sunita Chandrasekaran, with Professor Benjamin E. Bagozzi serving as co-PI.
Grant detailsRecent Work
Recent peer-reviewed papers, with replication data and code where available.
Almquist, Z.W., Bagozzi, B.E., Blinova, D., and Brown, Z.
Network Science · 2026
Blinova, D. and Bagozzi, B.E.
The Information Society · 2026
Chandna, S., Bagozzi, B.E., and Chatterjee, S.
IEEE Transactions on Network Science and Engineering · 2026
News & Updates
Announcements, project milestones, publications, and lab updates.
The lab's R package for underdispersed count data, now with a documentation site.
Restricted-access release on Zenodo with Qile Wang, Matthew Mauriello and colleagues.
Inflated ordered probit and logit models, including the zero-inflated ordered probit.
Join the Lab
Graduate and undergraduate students in political science, data science, and related fields are welcome to reach out.